Data Sheet 1_A home-based EEG neurofeedback treatment for chronic neuropathic pain—a pilot study.docx by Mohamed Sakel (9416397)

“…Mood scores showed a significant decrease in depression (p < 0.05), and pain catastrophizing (p < 0.05) scores improved significantly at post-intervention, with continued improvement at the first-month follow-up.…”

(a)Raw soil; (b) The grain size distribution. by Chenhao Li (822769)

“…Although increasing SHMP content improved the early strength, it led to a decrease in later strength, with the maximum late strength observed at 2% SHMP. …”

Data Sheet 1_Impact of a multifaceted intervention including a smart reminder system for intraoperative antibiotic re-dosing on surgical site infections in a Chinese tertiary care... by Cuiqiong Fan (17651671)

“…The proportion of intraoperative additional antibiotic administration also increased significantly (p = 0.003). Furthermore, the rate of SSIs decreased significantly after the intervention (p = 0.038).…”

Effect of the POM cycles on selected metabolites. by Bonnie A. McNeil (22331601)

Data_Sheet_1_Effects of a 30-min rest with a nap chair on task performance, sleepiness, and neurophysiological measures in men with suspected brain fatigue: a randomized controlled... by Minoru Fujino (12742196)

“…The Karolinska Sleepiness score significantly decreased after the nap-chair rest, and the between-treatment difference in the decrease was highly significant (P = 0.0004). …”

Transient suppression of autophagy in neurons impairs ITM. by Tong Yue (6033305)

(a) The impact of changing the epoch at which the proximity factor for infection clusters is activated on the validation infection coverage and <i>F</i>₁ measure. by Ibrahim Almakky (22530341)

Inhibition of lysosomal activity causes memory impairment. by Tong Yue (6033305)

“…<p><b>(A)</b>Heatmap of significantly down-regulated genes associated with the lysosomal signaling pathway between ND and HFD. …”

HFD impairs autophagic activity in fly brains. by Tong Yue (6033305)

Experimental design of this study. by Renya Kawakami (20469088)

“…However, only a few studies that investigated influences of male aging as well as male mating experience on their post-copulatory sexual selection. …”

All relevant data of this study. by Renya Kawakami (20469088)

“…However, only a few studies that investigated influences of male aging as well as male mating experience on their post-copulatory sexual selection. …”

Supplementary Material for: Off-label Use of Mycophenolate Mofetil in Immunoglobulin A Nephropathy: A Systematic Review and Meta-analysis by Feng L. (5056958)

“…Introduction: Mycophenolate mofetil (MMF) is widely used off-label in patients with immunoglobulin A nephropathy (IgAN), although the literature does not consistently agree on its efficacy and safety. …”

Preference for the EIA – conjoint results. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Marginal means – Pooled across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Sample attribute table. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Subgroup analysis – Political affiliation. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Sample scenario description. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

AMCEs – Pooled across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Methodological flowchart. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Preference for the EIA vs. ETA across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”